Understanding the complex relationships among human traits and diseases is a fundamental goal of epidemiology. Randomized controlled trials and longitudinal studies are time-consuming and expensive, so many potential risk factors are studied using cross-sectional correlations studies at a single time point. Obtaining causal inferences from such studies can be challenging due to issues such as confounding and reverse causation, which can lead to spurious associations and mask the effects of real risk factors [1, 2]. Genetics can help elucidate cause and effect, since inherited genetic risks cannot be subject to reverse causation and are correlated with a smaller list of confounders.
